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Vammen L, Munch Johannsen C, Magnussen A, Povlsen A, Riis Petersen S, Azizi A, Løfgren B, Andersen LW, Granfeldt A. Cardiac Arrest in Pigs With 48 hours of Post-Resuscitation Care Induced by 2 Methods of Myocardial Infarction: A Methodological Description. J Am Heart Assoc 2021; 10:e022679. [PMID: 34854307 PMCID: PMC9075364 DOI: 10.1161/jaha.121.022679] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Background Systematic reviews have disclosed a lack of clinically relevant cardiac arrest animal models. The aim of this study was to develop a cardiac arrest model in pigs encompassing relevant cardiac arrest characteristics and clinically relevant post‐resuscitation care. Methods and Results We used 2 methods of myocardial infarction in conjunction with cardiac arrest. One group (n=7) had a continuous coronary occlusion, while another group (n=11) underwent balloon‐deflation during arrest and resuscitation with re‐inflation after return of spontaneous circulation. A sham group was included (n=6). All groups underwent 48 hours of intensive care including 24 hours of targeted temperature management. Pigs underwent invasive hemodynamic monitoring. Left ventricular function was assessed by pressure‐volume measurements. The proportion of pigs with return of spontaneous circulation was 43% in the continuous infarction group and 64% in the deflation‐reinflation group. In the continuous infarction group 29% survived the entire protocol while 55% survived in the deflation‐reinflation group. Both cardiac arrest groups needed vasopressor and inotropic support and pressure‐volume measurements showed cardiac dysfunction. During rewarming, systemic vascular resistance decreased in both cardiac arrest groups. Median [25%;75%] troponin‐I 48 hours after return of spontaneous circulation, was 88 973 ng/L [53 124;99 740] in the continuous infarction group, 19 661 ng/L [10 871;23 209] in the deflation‐reinflation group, and 1973 ng/L [1117;1995] in the sham group. Conclusions This article describes a cardiac arrest pig model with myocardial infarction, targeted temperature management, and clinically relevant post‐cardiac arrest care. We demonstrate 2 methods of inducing myocardial ischemia with cardiac arrest resulting in post‐cardiac arrest organ injury including cardiac dysfunction and cerebral injury.
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Affiliation(s)
- Lauge Vammen
- Department of Anesthesiology and Intensive Care Aarhus University Hospital Aarhus Denmark.,Department of Clinical Medicine Aarhus University Aarhus Denmark
| | - Cecilie Munch Johannsen
- Department of Anesthesiology and Intensive Care Aarhus University Hospital Aarhus Denmark.,Department of Clinical Medicine Aarhus University Aarhus Denmark
| | | | - Amalie Povlsen
- Department of Clinical Medicine Aarhus University Aarhus Denmark.,Department of Cardiothoracic Anesthesia Copenhagen University HospitalRigshospitalet Denmark Copenhagen Denmark
| | | | - Arezo Azizi
- Department of Clinical Medicine Aarhus University Aarhus Denmark
| | - Bo Løfgren
- Department of Clinical Medicine Aarhus University Aarhus Denmark.,Research Center for Emergency Medicine Aarhus University Hospital Aarhus Denmark.,Department of Internal Medicine Randers Regional Hospital Randers Denmark
| | - Lars W Andersen
- Department of Anesthesiology and Intensive Care Aarhus University Hospital Aarhus Denmark.,Department of Clinical Medicine Aarhus University Aarhus Denmark.,Research Center for Emergency Medicine Aarhus University Hospital Aarhus Denmark.,Prehospital Emergency Medical Services Central Denmark Region Aarhus Denmark
| | - Asger Granfeldt
- Department of Anesthesiology and Intensive Care Aarhus University Hospital Aarhus Denmark.,Department of Clinical Medicine Aarhus University Aarhus Denmark
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Yang Q, Li M, Huang Z, Xie Z, Wang Y, Ling Q, Liu X, Tang W, Jiang L, Yang Z. Validation of spectral energy for the quantitative analysis of ventricular fibrillation waveform to guide defibrillation in a porcine model of cardiac arrest and resuscitation. J Thorac Dis 2019; 11:3853-3863. [PMID: 31656658 DOI: 10.21037/jtd.2019.09.18] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Background The amplitude spectrum area (AMSA), a frequency-domain ventricular fibrillation (VF) waveform metric, can predict successful defibrillation and the return of spontaneous circulation (ROSC) after defibrillation attempts. We aimed to investigate the validation of Spectral Energy for the quantitative analysis of the VF waveform to guide defibrillation in a porcine model of cardiac arrest and compare it with the AMSA metric. In addition, we sought to determine the effects of epinephrine and cardiopulmonary resuscitation (CPR) on AMSA and Spectral Energy. Methods Sixty male domestic pigs weighing 35 to 45 kg were involved in this study. VF was initially untreated for 10 min followed by 6 min of CPR. Epinephrine was administered to the animals after 2 min of CPR. After the CPR, a single 120-J biphasic shock was applied to the animals. AMSA and Spectral Energy values were measured every minute from the electrocardiogram (ECG) to defibrillation. Receiver operating characteristic (ROC) curves were calculated for both the Spectral Energy and AMSA methods. Results Spectral Energy and AMSA values gradually decayed during untreated VF in all the animals. However, after the application of CPR and epinephrine, Spectral Energy and AMSA values were significantly increased in animals which were later successfully defibrillated, but did not increase in animals in which defibrillation was unsuccessful. The ROC curves showed that the Spectral Energy and AMSA methods possessed similar levels of sensitivity and specificity in predicting defibrillation success (P<0.001). Conclusions Both the Spectral Energy and AMSA methods accurately predict successful defibrillation. Moreover, increases in the value of either Spectral Energy or AMSA after application of CPR and epinephrine may also predict successful defibrillation.
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Affiliation(s)
- Qiyu Yang
- School of Automation, Guangdong University of Technology, Guangzhou 510006, China
| | - Ming Li
- School of Automation, Guangdong University of Technology, Guangzhou 510006, China
| | - Zhaolan Huang
- School of Automation, Guangdong University of Technology, Guangzhou 510006, China
| | - Zhuoyan Xie
- School of Automation, Guangdong University of Technology, Guangzhou 510006, China
| | - Yue Wang
- Department of Emergency Medicine, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China
| | - Qin Ling
- Department of Emergency Medicine, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China
| | - Xuefen Liu
- Department of Emergency Medicine, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China
| | - Wanchun Tang
- Department of Emergency Medicine, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China.,Weil Institute of Emergency and Critical Care Research, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA
| | - Longyuan Jiang
- Department of Emergency Medicine, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China
| | - Zhengfei Yang
- Department of Emergency Medicine, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China.,Weil Institute of Emergency and Critical Care Research, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA.,Department of Emergency Medicine, Zengcheng District People's Hospital of Guangzhou, Guangzhou 511300, China
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Nakagawa Y, Amino M, Inokuchi S, Hayashi S, Wakabayashi T, Noda T. Novel CPR system that predicts return of spontaneous circulation from amplitude spectral area before electric shock in ventricular fibrillation. Resuscitation 2017; 113:8-12. [PMID: 28104427 DOI: 10.1016/j.resuscitation.2016.12.025] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2016] [Revised: 11/30/2016] [Accepted: 12/21/2016] [Indexed: 12/01/2022]
Abstract
AIM Amplitude spectral area (AMSA), an index for analysing ventricular fibrillation (VF) waveforms, is thought to predict the return of spontaneous circulation (ROSC) after electric shocks, but its validity is unconfirmed. We developed an equation to predict ROSC, where the change in AMSA (ΔAMSA) is added to AMSA measured immediately before the first shock (AMSA1). We examine the validity of this equation by comparing it with the conventional AMSA1-only equation. METHOD We retrospectively investigated 285 VF patients given prehospital electric shocks by emergency medical services. ΔAMSA was calculated by subtracting AMSA1 from last AMSA immediately before the last prehospital electric shock. Multivariate logistic regression analysis was performed using post-shock ROSC as a dependent variable. RESULTS Analysis data were subjected to receiver operating characteristic curve analysis, goodness-of-fit testing using a likelihood ratio test, and the bootstrap method. AMSA1 (odds ratio (OR) 1.151, 95% confidence interval (CI) 1.086-1.220) and ΔAMSA (OR 1.289, 95% CI 1.156-1.438) were independent factors influencing ROSC induction by electric shock. Area under the curve (AUC) for predicting ROSC was 0.851 for AMSA1-only and 0.891 for AMSA1+ΔAMSA. Compared with the AMSA1-only equation, the AMSA1+ΔAMSA equation had significantly better goodness-of-fit (likelihood ratio test P<0.001) and showed good fit in the bootstrap method. CONCLUSIONS Post-shock ROSC was accurately predicted by adding ΔAMSA to AMSA1. AMSA-based ROSC prediction enables application of electric shock to only those patients with high probability of ROSC, instead of interrupting chest compressions and delivering unnecessary shocks to patients with low probability of ROSC.
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Affiliation(s)
- Yoshihide Nakagawa
- Department of Emergency and Critical Care Medicine, Tokai University School of Medicine, 143 Shimokasuya, Isehara, Kanagawa 259-1193, Japan.
| | - Mari Amino
- Department of Emergency and Critical Care Medicine, Tokai University School of Medicine, 143 Shimokasuya, Isehara, Kanagawa 259-1193, Japan
| | - Sadaki Inokuchi
- Department of Emergency and Critical Care Medicine, Tokai University School of Medicine, 143 Shimokasuya, Isehara, Kanagawa 259-1193, Japan
| | - Satoshi Hayashi
- Nihon Kohden Co., 1-31-4 Nishi-Ochiai, Shinjuku-ku, Tokyo 161-8560, Japan
| | | | - Tatsuya Noda
- Department of Public Health, Health Management and Policy, Nara Medical University, 840 Shijou-cho, Kashihara-shi, Nara 634-0813, Japan
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